# Reefy supported hardware

Choose a PC, storage, network, and GPU configuration that fits your workload.

Reefy uses one image across small mini-PCs, repurposed laptops, custom GPU
workstations, and rack servers. Hardware support still depends on the Linux
kernel, included firmware, and the workload you intend to run.

## Baseline requirements

| Component | Minimum | Practical guidance |
|---|---:|---|
| CPU | x86-64 | Modern Intel and AMD systems are the primary target |
| Memory | 4 GB | Use 16 GB or more for several apps or local models |
| Boot media | 8 GB USB | A reliable USB 3 drive improves boot and update speed |
| Network | Ethernet or supported Wi-Fi | Ethernet is recommended for first boot and servers |
| Data storage | Optional internal SSD or NVMe | Recommended for models, recordings, and persistent app data |

ARM systems are not supported by the current public image.

## CPU and memory

AI agents that call remote model providers need much less compute than local
inference. A small four-core mini-PC with 8 to 16 GB of RAM can run agents,
development tools, monitoring, and home applications.

Local language models need enough memory for model weights, runtime overhead,
and the desired context window. Size the machine for the model rather than for
Reefy itself.

## NVIDIA GPUs

Reefy includes NVIDIA kernel drivers, firmware, CUDA userspace, and Container
Device Interface generation. GPU-aware catalog applications can request the
device without a separate driver installation.

GPU compatibility varies by architecture and driver support. Before buying a
card specifically for Reefy, verify that its generation is supported by the
driver version in the current Reefy release.

For local LLMs, available VRAM often matters more than peak gaming performance.
If a model does not fit completely in VRAM, the runtime may use system memory or
CPU execution with a substantial performance cost.

## Intel integrated GPU and NPU

Intel graphics and NPU devices are useful for media and inference experiments,
but application support depends on the runtime. The Reefy video benchmark
includes OpenVINO GPU and NPU paths so performance and detection parity can be
measured rather than assumed.

See the [AI video inference benchmark](/benchmarks/ai-video-inference).

## Storage

Running Reefy from USB leaves internal drives available for encrypted data.
Adopted storage uses LUKS2 encryption, LVM thin provisioning, and XFS. Fast NVMe
storage helps model loading, video recording, development environments, and
backup snapshots.

The USB drive is operationally important when it contains key material. Keep a
recovery plan and do not treat an unknown low-quality flash drive as permanent
server media.

## Firmware settings

- Use UEFI boot mode.
- Disable Secure Boot for the current public image.
- Enable hardware virtualization when applications need KVM.
- Enable the integrated GPU if you plan to use it alongside a discrete GPU.
- Configure automatic power recovery if the device should return after an
  outage.

## What "supported" means

The public image targets a broad x86-64 hardware range, but it cannot promise
that every peripheral in every PC has a working upstream driver. A machine is
confirmed only after its storage, network, sensors, accelerators, suspend
behavior, and update path have been exercised.